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BLDC 모터 구동을 위한 신경회로망 PI파라미터 자기 동조 시뮬레이터
배은경(E. K. Bae),권중동(J. D. Kwon),김태우(T. W. Kim),김대균(D. K. Kim),전지용(J. Y. Chun),이승환(S. H. Lee),이훈구(H. G. Lee),김용주(Y. J. Kim),한경희(K. H. Han) 대한전기학회 2006 대한전기학회 학술대회 논문집 Vol.2006 No.7
In this paper proposed to Neural network PI self-tuning direct controller using Error beck propagation algorithm. Proposed controller applies to speed controller and current controller. Also, this built up the interface environment to drive it simply and exactly in any kind of reference, environment fluent and parameter transaction of BLDC motor. Neural network PI self-tuning simulator using Visual C++ and Matlab Simulation is organized to construct this environment. Built-u-p interface has it's own purpose that even the user who don't have the accurate knowledge of neural network can embody operation characteristic rapidly and easily.
이상현(S. H. Lee),배은경(E. K. Bae),신철준(C. J. Sin),전기영(K. Y. Jeon),전지용(J. Y. Jeon),오봉환(B. H. Oh),이훈구(H. G. Lee),한경희(K. H. Han) 전력전자학회 2007 전력전자학술대회 논문집 Vol.- No.-
In this paper, The authors apply a state feedback control using an optimal control theory to improve the stability of the control and the dynamic response of the DC-DC converter system with a number of different loads. To execute a this state feedback control, The authors present the pole placement technique using Linear Quadratic Regulator(LQR) to optimally control the system. An integrator can also be included in the open-loop path in order to minimize the steady-state error of the output voltage. To confirm the superiority of the controller, The simulation results are presented.